Human computer interaction has been revolutionized by the introduction of the graphical user interface (GUI). Thereby, an efficient means was provided for presenting information to a user with a bandwidth that immensely exceeded any prior channels. Over the years the speed at which information can be presented has increased further through colour screens, enlarged displays, intelligent graphical objects (e.g. pop-up windows), window tabs, menus, toolbars, etc. During this time, however, the input devices have remained essentially unchanged, i.e. the keyboard and the pointing device (e.g. the mouse, track ball or touch pad). In recent years, handwriting devices have been introduced (e.g. in the form of a stylus or graphical pen). Nevertheless, while output bandwidth has multiplied several times, the input bandwidth has been substantially unchanged. Consequently, a severe asymmetry in the communication bandwidth in the human computer interaction has developed.
In order to decrease this bandwidth asymmetry as well as to improve and facilitate the user interaction, various attempts have been made to use eye-tracking for such purposes. Monitoring or tracking eye movements and detecting a person's gaze point (as used herein, the point in space at which the person is looking) can be an important information source in analysing the behaviour or consciousness of the person. It can be used both for evaluating the object at which the person is looking and for evaluating the respective person. By implementing an eye tracking device in e.g. a laptop, the interaction possibilities between the user and the different software applications run on the computer can be significantly enhanced.
Using the Internet, a computer user has access to a vast amount of information. However, selecting and identifying the most relevant or most interesting information can be a difficult challenge for the user. By utilizing gaze tracking or eye tracking data, the process of searching for such relevant or interesting information can be made more efficient and can be customized to the user needs and requirements.
In U.S. Pat. No. 6,437,758 to Nielsen et al., methods and system for dynamic adjustment of presented information based on eye-tracking data are disclosed. According to U.S. Pat. No. 6,437,758, articles and advertisements are categorized according to topics. Using gaze tracking, an information provider can determine the user's interest in each displayed article or advertisement. Then, by using the topics categorizing the presented information, the information provider can dynamically adjust the selection of subsequent information presented to the user. In an example, a user read scientific based articles but did not spend any time reading other articles or advertisements. In this case, the information provider populates the next page of information presented to the user with articles and advertisements that have similar topics as the previously read information.
Other prior art methods and systems have also been presented. In for example U.S. Pat. No. 7,881,493 to Edwards et al. customized web content is presented for a user based on eye-tracking data. The characteristics of an application are dynamically modified based on an interpretation of eye-tracking data. In U.S. Pat. No. 7,576,757 to Kariathungal et al., most read images are identified based on viewing time. Reading times for several images can be determined and a priority can be assigned to the images based on the reading time. The images can be arranged on a display based on the priority.
U.S. Pat. No. 6,608,615 to Martins discloses a method and system for passively tracking a user's eye gaze while browsing a web page to modify the presentation of the web page based on the tracked gaze. By combining historical information about a user's direction of gaze on individual cached web pages, a browser is enabled to represent regions of a web page that have been previously glanced at by the user in a modified manner.
In U.S. Pat. No. 7,818,324 to Held et al., methods and systems for searching for content on networks and computer devices are disclosed. Search engines, such as the Google™ search engine enables a user to search for information on a network via a web site by entering a search query. A search engine searches a generated searchable index and identifies resources of a corpus of resources (i.e. a collection of resources e.g. web pages, images, videos, and the like stored on one or more information host) that is responsive to the search query. By indexing the resources an efficient searching can be achieved.
The full potential of the information content of the eye tracking or gaze tracking data is not utilized in these prior art methods and systems. For example, in the methods and systems of U.S. Pat. No. 6,437,758 only topic based presentation of related information such as articles and advertisements is provided.
Accordingly, there is a need within the art for improved methods and system that provides a more efficient use of gaze tracking data for user customized information search and information presentation. There is further a need within the art for methods and system that provides an efficient use of gaze tracking data to facilitate and improve information search and information presentation.